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Record W4390692437 · doi:10.1109/tap.2024.3349771

ASIC-Enabled Programmable Metasurfaces—Part 2: Performance and Synthesis

2024· article· en· W4390692437 on OpenAlexaff
Kypros M. Kossifos, Julius Georgiou, Marco A. Antoniades

Bibliographic record

VenueIEEE Transactions on Antennas and Propagation · 2024
Typearticle
Languageen
FieldMaterials Science
TopicMetamaterials and Metasurfaces Applications
Canadian institutionsToronto Metropolitan UniversityUniversity of Toronto
FundersEuropean Regional Development Fund
KeywordsApplication-specific integrated circuitWavefrontWirelessPolarization (electrochemistry)OpticsPhysicsReconfigurabilityComputer scienceComputer hardwareTelecommunications

Abstract

fetched live from OpenAlex

A multifunctional and reconfigurable programmable metasurface (PMSF) enabled by an application-specific integrated circuit (ASIC) that targets smart wireless environment applications is presented in this work. In the accompanying paper, in Part 1, the PMSF design experimentally demonstrated the ability to control independently the magnitude and phase of the reflection coefficients for both orthogonal polarizations. Here, this ability is exploited to demonstrate programmable electromagnetic wavefront manipulation. A fast and accurate synthesis method using a 2-D single-iteration discrete Fourier transform (DFT) for producing multiple pencil beams, each with different polarizations, is presented. Each pencil beam can have a linear, right-handed circular polarization, left-handed circular polarization, or even elliptical polarization. The synthesis method is ideal for wireless reconfigurable environments enabled by the PMSF, where the number of unit cells is very large. The PMSF aims to be a single component, installed not only in the surrounding walls to reconfigure the wireless environment, but also at the transmitting antennas. The design is experimentally verified by producing a mixture of linearly polarized and circularly polarized wavefronts, and also single, dual, and simultaneous orbital angular momentum (OAM) pencil beams are experimentally shown.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.064
Threshold uncertainty score0.539

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.021
GPT teacher head0.241
Teacher spread0.220 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations14
Published2024
Admission routes1
Has abstractyes

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